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Soil Erosion Assessment Risk Using Modeling and Spectral Indices: A Case Study of Wadi Rmel Watershed, Northeastern Tunisia.

Authors :
Jarray, Fathia
Hermassi, Taoufik
Kotti, Mohamed Lassaad
Mechergui, Mohamed
Source :
Journal of the Indian Society of Remote Sensing; Jul2024, Vol. 52 Issue 7, p1611-1621, 11p
Publication Year :
2024

Abstract

In Mediterranean regions, soil erosion is one of the most serious challenges with land degradation. The current work aims to study the water erosion in the watershed of Wadi Rmel located in the North-East of Tunisia, using the SWAT model, RUSLE method and, PAP/RAC approach for the year 2020. These methods are concentrated on the integration of factors influencing soil erosion and then validated by chosen spectral indices (NDVI, IB and, MSAVI), that are the most used to characterize the state of soil degradation. SWAT model demonstrates that the most eroded zones are located in South-West zones, in sub-basins number 10, 17 and 26. These areas presented a degraded vegetation cover with an NDVI value near zero. Moreover, the resulting map of the RUSLE method shows that the most erosive zone is located in the regions of the southwest. This part presents a high percentage of BI, more than 20%. On the other hand, the analysis of the erosive map conditions, presented by the PAP/RAC guidelines, shows also that the very high erosive state is located in southwestern areas with various uncovered zones. The same spatial distribution of soil erosion is found by the three used methods and confirmed by the spectral indices. Finally, this study results are beneficial for decision-makers to identify priority areas for intervention and to evaluate the existing management plans. Moreover, the application of spectral indices provides a useful tool to predict soil erosion hazard and to validate modeling results in case of the absence of field missions and observations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0255660X
Volume :
52
Issue :
7
Database :
Complementary Index
Journal :
Journal of the Indian Society of Remote Sensing
Publication Type :
Academic Journal
Accession number :
178276305
Full Text :
https://doi.org/10.1007/s12524-024-01878-2